code: def test_set_uniform_vacancy_probabilities_of_max_displacements(self):
      # arrange
      src_classes = {"schinken": 0, "eier": 0, "spam": 1}
      trg_classes = {"ham": 0, "eggs": 1, "spam": 2}
      corpus = [
          AlignedSent(
              ["ham", "eggs"], ["schinken", "schinken", "eier"]
          ),
          AlignedSent(
              ["spam", "spam", "spam", "spam"], ["spam", "spam"]
          ),
      ]
      model5 = IBMModel5(corpus, 0, src_classes, trg_classes)
  
      # act
      model5.set_uniform_probabilities(corpus)
  
      # assert
      # number of vacancy difference values =
      #     2 * number of words in longest target sentence
      expected_prob = 1.0 / (2 * 4)
  
      # examine the boundary values for (dv, max_v, trg_class)
      self.assertEqual(
          model5.head_vacancy_table[4][4][0], expected_prob
      )
      self.assertEqual(
          model5.head_vacancy_table[-3][1][2], expected_prob
      )
      self.assertEqual(
          model5.non_head_vacancy_table[4][4][0], expected_prob
      )
      self.assertEqual(
          model5.non_head_vacancy_table[-3][1][2], expected_prob
      )
  
file_path: nltk/nltk/test/unit/translate/test_ibm5.py
imports: import unittest
  from collections import defaultdict
  from nltk.translate import AlignedSent, IBMModel, IBMModel4, IBMModel5
  from nltk.translate.ibm_model import AlignmentInfo
label_desc: Use image node_id 1 for calling the TestIBMModel5 obj's underlying member method code with example usage: obj.test_set_uniform_vacancy_probabilities_of_max_displacements() without return types